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DISCO-DJ I: a differentiable Einstein-Boltzmann solver for cosmology

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arxiv 2311.03291 v2 pith:6527PNEX submitted 2023-11-06 astro-ph.CO

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keywords solverdifferentiablecosmologydarkeinstein-boltzmannparametersadditionalcosmological
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We present the Einstein-Boltzmann module of the DISCO-DJ (DIfferentiable Simulations for COsmology - Done with JAX) software package. This module implements a fully differentiable solver for the linearised cosmological Einstein-Boltzmann equations in the JAX framework, and allows computing Jacobian matrices of all solver output with respect to all input parameters using automatic differentiation. This implies that along with the solution for a given set of parameters, the tangent hyperplane in parameter space is known as well, which is a key ingredient for cosmological inference and forecasting problems as well as for many other applications. We discuss our implementation and demonstrate that our solver agrees at the per-mille level with the existing non-differentiable solvers CAMB and CLASS, including massive neutrinos and a dark energy fluid with parameterised equation of state. We illustrate the dependence of various summary statistics in large-scale structure cosmology on model parameters using the differentiable solver, and finally demonstrate how it can be easily used for Fisher forecasting, with a forecast for Euclid as an example. Since the implementation is significantly shorter and more modular than existing solvers, we believe it will be more straightforward to extend our solver to include additional physics, such as additional dark energy and dark matter models, modified gravity, or other non-standard physics in the future.

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Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. DISCO-DJ II: a differentiable particle-mesh code for cosmology

    astro-ph.CO 2025-10 conditional novelty 6.0 of 10

    A GPU-accelerated, differentiable particle-mesh N-body code achieves per-cent-level power-spectrum accuracy with few time steps and recovers sigma_8 plus initial conditions from a noisy mock field.

  2. Differentiable Halo Mass Prediction and the Cosmology-Dependence of Halo Mass Functions

    astro-ph.CO 2025-07 conditional novelty 6.0 of 10

    A differentiable U-Net predicts halo mass functions and their cosmology derivatives from initial density fields, matching finite-difference gradients of simulations and emulators to within model scatter.

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